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I have to warn you though...much of the reason the NFL has likely resisted the heavy integration of analytics into the process is because as soon as they get a real statistics expert in the office that person is more likely to spend his days saying "no" than saying "yes". A person with a firm grounding in statistics would tend to lament the insufficient sample sizes and lack of statistical significance involved in any study involving football-related data sets. Some of the stuff you're asking about (e.g. 'recent trends') strikes me as more likely to fall into traps than to be meaningful, most often due to insufficient sample size. I think once you get beyond that barrier if a statistics guy really begins to understand the sport and the drivers of success then perhaps he can start to figure out more valuable things that analytics actually can offer the sport instead of just pointing out the endless list of things it can't.

Just my point of view on the matter. I work in equities research, was an econ major in college. I don't have what I would deem a professionally strong statistics or math background (which to me would entail a graduate degree or at least undergraduate degree in math or stats), but I do have some background there and understanding of them.

I think you're more likely to get mostly "inconclusives" rather than "no's." I've seen very few analytics that are powerful enough to give firm answers one way or the other and if you're are going to use them they should be used as a starting point rather than the deciding factor.

I think James would likely still be around after #19 but before we pick again at #50.....so if the top guys are off the board at #19, maybe try to trade down and get James a little later and another quality guy before we pick again at #50. I still think there is a decent possibility that Lewan or Zack Martin drops down to us.

I have to warn you though...much of the reason the NFL has likely resisted the heavy integration of analytics into the process is because as soon as they get a real statistics expert in the office that person is more likely to spend his days saying "no" than saying "yes". A person with a firm grounding in statistics would tend to lament the insufficient sample sizes and lack of statistical significance involved in any study involving football-related data sets. Some of the stuff you're asking about (e.g. 'recent trends') strikes me as more likely to fall into traps than to be meaningful, most often due to insufficient sample size. I think once you get beyond that barrier if a statistics guy really begins to understand the sport and the drivers of success then perhaps he can start to figure out more valuable things that analytics actually can offer the sport instead of just pointing out the endless list of things it can't.

Just my point of view on the matter. I work in equities research, was an econ major in college. I don't have what I would deem a professionally strong statistics or math background (which to me would entail a graduate degree or at least undergraduate degree in math or stats), but I do have some background there and understanding of them.

I literally had to re-read this post twice shows my mathematical knowledge and understanding..

I agree that sample size is a limiting factor in this. That's why this should be taken with a grain of salt. Not an "end all be all" kind of thing. Rather, a way to look at things. How can you look at recent trends that have a small sample size? Not a rhetorical question. I believe things like recent trends should be something to look at and try and draw conclusions from. At most, it would be a very small piece of the pie. For example the trend of Right Tackles. I think it's safe to say that the position is trending, and good ones are going higher now than, say in 2004.

I'm not a statistics or analytics guy trying to apply football knowledge I barely understand. I'm a football guy trying to apply statistics or analytics I barely understand.

I'm not trying to come up with a money ball scenario or formula. Just look at trends and the way successful teams are doing things, and what conclusions can be drawn from it. But I would rely heavily on my football knowledge when doing this. Not some "holy grail formula"

I think you're more likely to get mostly "inconclusives" rather than "no's." I've seen very few analytics that are powerful enough to give firm answers one way or the other and if you're are going to use them they should be used as a starting point rather than the deciding factor.

This is your best post I've seen. I think they should be used as a starting point to look at way things are being done. For example, trying to find strange correlation between crazy statistics and how much they equate how much a QB is responsible for wins by using YPA is beyond ridiculous.

Anything shouright/gravity has posted is rubbish

However, stats like the correlation beween turnover differential and winning is a valid one.

I've found the deeper you dive into formulas, the farther away you get from football, and the less weight it will hold with football people.

Simple stats like 3rd down % redzone % and turnovers and how they relate to winning are good places to start. A lot easier to measure.